Association of Primary Care Physicians’ Individual- and Community-Level Characteristics With Contraceptive Service Provision to Medicaid Beneficiaries

This cross-sectional study examines the factors associated with primary care physicians providing contraceptive services to Medicaid beneficiaries.


A. Initial data quality assessment
To perform an initial assessment of states' data quality, we referred to Data Quality (DQ) Atlas (see eTable 4). Since being able to identify a physician that provided a particular service is crucial for our analysis, we required states to have 'low concern' status on the topic 'Servicing Provider NPI -Other Services (OT) File' (19 states) and on the topic 'Prescribing Provider NPI -Pharmacy (RX) File' (44 states).
However, only 16 states met our selection criterion and relaxing it to include states with 'medium concern' data quality would have added only 13 more states. Therefore, to expand our sample size, we performed additional data cleaning based on information in the T-MSIS Annual Provider (APR) File.

B. Data cleaning I. Understanding T-MSIS file structure
Following is a brief summary of the contents of files in T-MSIS 2016.
a) Other Services (OT) file: This file includes encounter data. It includes: a. records for physician services, outpatient hospital institutional utilization, lab/X-ray, clinic services etc. b. diagnosis and procedure codes for an encounter c. billing and servicing provider National Provider Identifiers (NPIs) d. billing and servicing state Provider Identification Numbers: These are state-assigned unique numbers to identify the provider who billed or provided a particular service b) Pharmacy (RX) file: This file includes information about prescriptions filled for Medicaid beneficiaries.

II. Linking NPIs with State Provider Numbers
Since each physician has a unique NPI and a unique Provider Identification Number (in each state), it was possible to create a linkage between these two data elements.

States Included Criterion
All (50 states + Puerto Rico + DC) 'Low concern' status after filling in NPI and after additional data quality

III. Filling in missing NPIs in encounter and prescription data
Next, in cases where the servicing provider NPI was missing for a particular claim but the servicing state Provider Identification Number was present, we used the 'NPI-State Provider Identification Number' linkage and filled in the servicing providing NPI for that particular claim (see figure below).

eFigure 3. An Example of Filling in NPIs in T-MSIS Encounter Claims
This enabled us to improve the quality of many states' encounter data on servicing and prescribing provider NPIs.
We would like to note that state categorization based on missingness of state-assigned Provider Identification Numbers is currently not available in the DQ Atlas.

IV. Reassessing states' data quality
As the final step of state selection for analysis, we performed additional checks on states' data.
First, we calculated the percentage of each state's total submitted claim lines that had missing servicing providing NPIs, after performing the data cleaning described earlier. We categorized states' OT file data as having 'low concern' if less than 10% of their claim lines had missing servicing NPIs. Similarly, states which had missing servicing provider NPIs in 10 to 20% of the claim lines were categorized as having 'medium concern' data. States which did not have servicing NPIs in 20 to 50% of their claim lines were categorized as having 'high concern' data and if more than 50% of claim lines had missing servicing provider NPIs, data from such states was categorized as 'unusable'. The categorization used for RX files was similar (0-10% claim lines missing prescribing NPIs = low concern; 10-20% missing = medium concern; 20-50% missing = high concern; more than 50% missing = unusable) We excluded states that had 'high concern' or 'unusable' data quality status for either file. The result of this recategorization of states is summarized in eTable 5.
During this process, we also checked for unusual data patterns and for data anomalies. We found that Minnesota's T-MSIS 2016 OT file reported NPIs and State Provider Numbers of managed care organizations and not of individual providers in the 'Servicing Provider NPI' and 'Servicing Provider Identification Number' fields. Since this is inaccurate, we categorized Minnesota's data as 'unusable' for analysis. On the other hand, Mississippi's RX data had received 'unusable' status in the DQ Atlas since the 'Prescribing Provider NPI' filed in the state's OT file had a lot of missing data. After data cleaning, we were able to remedy this situation and we subsequently categorized Mississippi's data as 'low concern'. After performing data quality reassessment, our final analytical sample included the 44 states and Puerto Rico. We excluded 6 states (Arkansas, Florida, Maine, Minnesota, Pennsylvania, Rhode Island) and Washington, DC from the analysis.